论文信息 - openEBGM: An R Implementation of the Gamma-Poisson Shrinker Data Mining Model

openEBGM: An R Implementation of the Gamma-Poisson Shrinker Data Mining Model

Abstract We introduce the R package openEBGM, an implementation of the Gamma-Poisson Shrinker (GPS) model for identifying unexpected counts in large contingency tables using an empirical Bayes approach. The Empirical Bayes Geometric Mean (EBGM) and quantile scores are obtained from the GPS model estimates. openEBGM provides for the evaluation of counts using a number of different methods, including the model-based disproportionality scores, the relative reporting ratio (RR), and the proportional reporting ratio (PRR). Data squashing for computational efficiency and stratification for confounding variable adjustment are included. Application to adverse event detection is discussed.

John Ihrie | Travis Canida | J. Ihrie | Travis Canida | T. Canida

[1] David Madigan,et al. Bayesian Methods in Pharmacovigilance , 2010 .

[2] William DuMouchel,et al. Bayesian Data Mining in Large Frequency Tables, with an Application to the FDA Spontaneous Reporting System , 1999 .

[3] Ismaïl Ahmed,et al. Bayesian pharmacovigilance signal detection methods revisited in a multiple comparison setting , 2009, Statistics in medicine.

[4] R. O’Neill,et al. Use of Screening Algorithms and Computer Systems to Efficiently Signal Higher-Than-Expected Combinations of Drugs and Events in the US FDA’s Spontaneous Reports Database , 2002, Drug safety.

[5] Francesca Dominici,et al. Random effects models for identifying the most harmful medication errors in a large, voluntary reporting database , 2017 .

[6] William DuMouchel,et al. Empirical bayes screening for multi-item associations , 2001, KDD '01.

[7] W. DuMouchel,et al. Comparative Performance of Two Quantitative Safety Signalling Methods , 2006, Drug safety.

[8] Cedric E. Ginestet. ggplot2: Elegant Graphics for Data Analysis , 2011 .

[9] S. Evans,et al. Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports , 2001, Pharmacoepidemiology and drug safety.

[10] Marc Boyer,et al. Use of data mining at the Food and Drug Administration , 2016, J. Am. Medical Informatics Assoc..